Overview

Dataset statistics

Number of variables23
Number of observations940
Missing cells4815
Missing cells (%)22.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory169.0 KiB
Average record size in memory184.1 B

Variable types

Numeric20
DateTime1
Categorical2

Alerts

activity_level is highly overall correlated with fairly_active_minutes and 6 other fieldsHigh correlation
bmi is highly overall correlated with calories and 3 other fieldsHigh correlation
calories is highly overall correlated with bmi and 6 other fieldsHigh correlation
fairly_active_minutes is highly overall correlated with activity_level and 6 other fieldsHigh correlation
id is highly overall correlated with weight_kg and 1 other fieldsHigh correlation
light_active_distance is highly overall correlated with lightly_active_minutes and 3 other fieldsHigh correlation
lightly_active_minutes is highly overall correlated with light_active_distance and 3 other fieldsHigh correlation
moderately_active_distance is highly overall correlated with activity_level and 6 other fieldsHigh correlation
sedentary_minutes is highly overall correlated with bmi and 4 other fieldsHigh correlation
total_distance is highly overall correlated with activity_level and 9 other fieldsHigh correlation
total_minutes_asleep is highly overall correlated with sedentary_minutes and 1 other fieldsHigh correlation
total_steps is highly overall correlated with activity_level and 9 other fieldsHigh correlation
total_time_in_bed is highly overall correlated with sedentary_minutes and 1 other fieldsHigh correlation
tracker_distance is highly overall correlated with activity_level and 9 other fieldsHigh correlation
very_active_distance is highly overall correlated with activity_level and 6 other fieldsHigh correlation
very_active_minutes is highly overall correlated with activity_level and 9 other fieldsHigh correlation
weight_kg is highly overall correlated with bmi and 5 other fieldsHigh correlation
weight_pounds is highly overall correlated with bmi and 5 other fieldsHigh correlation
total_sleep_records is highly imbalanced (65.6%)Imbalance
daily_average_heartrate has 606 (64.5%) missing valuesMissing
total_minutes_asleep has 530 (56.4%) missing valuesMissing
total_sleep_records has 530 (56.4%) missing valuesMissing
total_time_in_bed has 530 (56.4%) missing valuesMissing
bmi has 873 (92.9%) missing valuesMissing
weight_kg has 873 (92.9%) missing valuesMissing
weight_pounds has 873 (92.9%) missing valuesMissing
total_steps has 77 (8.2%) zerosZeros
total_distance has 78 (8.3%) zerosZeros
tracker_distance has 78 (8.3%) zerosZeros
logged_activities_distance has 908 (96.6%) zerosZeros
very_active_distance has 413 (43.9%) zerosZeros
moderately_active_distance has 386 (41.1%) zerosZeros
light_active_distance has 85 (9.0%) zerosZeros
sedentary_active_distance has 858 (91.3%) zerosZeros
very_active_minutes has 409 (43.5%) zerosZeros
fairly_active_minutes has 384 (40.9%) zerosZeros
lightly_active_minutes has 84 (8.9%) zerosZeros

Reproduction

Analysis started2024-01-31 15:12:25.967182
Analysis finished2024-01-31 15:14:28.061360
Duration2 minutes and 2.09 seconds
Software versionydata-profiling v0.0.dev0
Download configurationconfig.json

Variables

id
Real number (ℝ)

HIGH CORRELATION 

Distinct33
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.8554074 × 109
Minimum1.5039604 × 109
Maximum8.8776894 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.5 KiB
2024-01-31T15:14:28.225255image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1.5039604 × 109
5-th percentile1.6245801 × 109
Q12.320127 × 109
median4.445115 × 109
Q36.9621811 × 109
95-th percentile8.7920097 × 109
Maximum8.8776894 × 109
Range7.373729 × 109
Interquartile range (IQR)4.6420541 × 109

Descriptive statistics

Standard deviation2.4248055 × 109
Coefficient of variation (CV)0.4994031
Kurtosis-1.2730307
Mean4.8554074 × 109
Median Absolute Deviation (MAD)2.418763 × 109
Skewness0.1771249
Sum4.5640829 × 1012
Variance5.8796816 × 1018
MonotonicityIncreasing
2024-01-31T15:14:28.489071image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
1503960366 31
 
3.3%
4319703577 31
 
3.3%
8583815059 31
 
3.3%
8378563200 31
 
3.3%
8053475328 31
 
3.3%
7086361926 31
 
3.3%
6962181067 31
 
3.3%
5553957443 31
 
3.3%
4702921684 31
 
3.3%
4558609924 31
 
3.3%
Other values (23) 630
67.0%
ValueCountFrequency (%)
1503960366 31
3.3%
1624580081 31
3.3%
1644430081 30
3.2%
1844505072 31
3.3%
1927972279 31
3.3%
2022484408 31
3.3%
2026352035 31
3.3%
2320127002 31
3.3%
2347167796 18
1.9%
2873212765 31
3.3%
ValueCountFrequency (%)
8877689391 31
3.3%
8792009665 29
3.1%
8583815059 31
3.3%
8378563200 31
3.3%
8253242879 19
2.0%
8053475328 31
3.3%
7086361926 31
3.3%
7007744171 26
2.8%
6962181067 31
3.3%
6775888955 26
2.8%
Distinct31
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size7.5 KiB
Minimum2016-04-12 00:00:00
Maximum2016-05-12 00:00:00
2024-01-31T15:14:28.765333image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:14:29.046350image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=31)

daily_average_heartrate
Real number (ℝ)

MISSING 

Distinct320
Distinct (%)95.8%
Missing606
Missing (%)64.5%
Infinite0
Infinite (%)0.0%
Mean75.974042
Minimum57.87
Maximum107.72
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.5 KiB
2024-01-31T15:14:29.317238image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum57.87
5-th percentile61.8545
Q167.5125
median75.22
Q381.9325
95-th percentile94.978
Maximum107.72
Range49.85
Interquartile range (IQR)14.42

Descriptive statistics

Standard deviation10.340623
Coefficient of variation (CV)0.13610732
Kurtosis0.078897821
Mean75.974042
Median Absolute Deviation (MAD)7.35
Skewness0.63378008
Sum25375.33
Variance106.92849
MonotonicityNot monotonic
2024-01-31T15:14:29.619163image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
75.22 3
 
0.3%
69.96 2
 
0.2%
64.49 2
 
0.2%
63.37 2
 
0.2%
77 2
 
0.2%
74.15 2
 
0.2%
75.33 2
 
0.2%
77.55 2
 
0.2%
76.02 2
 
0.2%
84.6 2
 
0.2%
Other values (310) 313
33.3%
(Missing) 606
64.5%
ValueCountFrequency (%)
57.87 1
0.1%
58.11 1
0.1%
58.37 1
0.1%
58.7 1
0.1%
59.2 1
0.1%
59.21 1
0.1%
59.23 1
0.1%
59.46 1
0.1%
60.27 1
0.1%
60.39 1
0.1%
ValueCountFrequency (%)
107.72 1
0.1%
107.09 1
0.1%
106.4 1
0.1%
105.02 1
0.1%
104.67 1
0.1%
101.45 1
0.1%
100.43 1
0.1%
99.49 1
0.1%
99.15 1
0.1%
99.12 1
0.1%

total_steps
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct842
Distinct (%)89.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7637.9106
Minimum0
Maximum36019
Zeros77
Zeros (%)8.2%
Negative0
Negative (%)0.0%
Memory size7.5 KiB
2024-01-31T15:14:29.937852image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13789.75
median7405.5
Q310727
95-th percentile15485.1
Maximum36019
Range36019
Interquartile range (IQR)6937.25

Descriptive statistics

Standard deviation5087.1507
Coefficient of variation (CV)0.66603957
Kurtosis1.1691112
Mean7637.9106
Median Absolute Deviation (MAD)3446.5
Skewness0.65289494
Sum7179636
Variance25879103
MonotonicityNot monotonic
2024-01-31T15:14:30.226917image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 77
 
8.2%
244 2
 
0.2%
6708 2
 
0.2%
9167 2
 
0.2%
6175 2
 
0.2%
10538 2
 
0.2%
1510 2
 
0.2%
8538 2
 
0.2%
7937 2
 
0.2%
4363 2
 
0.2%
Other values (832) 845
89.9%
ValueCountFrequency (%)
0 77
8.2%
4 1
 
0.1%
8 1
 
0.1%
9 1
 
0.1%
16 1
 
0.1%
17 1
 
0.1%
29 1
 
0.1%
31 1
 
0.1%
42 1
 
0.1%
44 1
 
0.1%
ValueCountFrequency (%)
36019 1
0.1%
29326 1
0.1%
27745 1
0.1%
23629 1
0.1%
23186 1
0.1%
22988 1
0.1%
22770 1
0.1%
22359 1
0.1%
22244 1
0.1%
22026 1
0.1%

total_distance
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct615
Distinct (%)65.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.4897021
Minimum0
Maximum28.03
Zeros78
Zeros (%)8.3%
Negative0
Negative (%)0.0%
Memory size7.5 KiB
2024-01-31T15:14:30.515896image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12.62
median5.245
Q37.7125
95-th percentile11.6565
Maximum28.03
Range28.03
Interquartile range (IQR)5.0925

Descriptive statistics

Standard deviation3.9246059
Coefficient of variation (CV)0.71490325
Kurtosis3.1130182
Mean5.4897021
Median Absolute Deviation (MAD)2.56
Skewness1.1262736
Sum5160.32
Variance15.402532
MonotonicityNot monotonic
2024-01-31T15:14:30.810212image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 78
 
8.3%
2.6 5
 
0.5%
0.01 5
 
0.5%
3.91 4
 
0.4%
4.95 4
 
0.4%
1.79 4
 
0.4%
4.33 4
 
0.4%
2.68 4
 
0.4%
3.51 4
 
0.4%
4.9 4
 
0.4%
Other values (605) 824
87.7%
ValueCountFrequency (%)
0 78
8.3%
0.01 5
 
0.5%
0.02 1
 
0.1%
0.03 2
 
0.2%
0.04 1
 
0.1%
0.08 1
 
0.1%
0.09 1
 
0.1%
0.1 1
 
0.1%
0.11 1
 
0.1%
0.13 1
 
0.1%
ValueCountFrequency (%)
28.03 1
0.1%
26.72 1
0.1%
25.29 1
0.1%
20.65 1
0.1%
20.4 1
0.1%
19.56 1
0.1%
19.34 1
0.1%
18.98 1
0.1%
18.25 1
0.1%
18.11 1
0.1%

tracker_distance
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct613
Distinct (%)65.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.4753511
Minimum0
Maximum28.03
Zeros78
Zeros (%)8.3%
Negative0
Negative (%)0.0%
Memory size7.5 KiB
2024-01-31T15:14:31.102190image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12.62
median5.245
Q37.71
95-th percentile11.6565
Maximum28.03
Range28.03
Interquartile range (IQR)5.09

Descriptive statistics

Standard deviation3.9072759
Coefficient of variation (CV)0.71361195
Kurtosis3.203889
Mean5.4753511
Median Absolute Deviation (MAD)2.555
Skewness1.1345496
Sum5146.83
Variance15.266805
MonotonicityNot monotonic
2024-01-31T15:14:31.379794image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 78
 
8.3%
2.6 5
 
0.5%
0.01 5
 
0.5%
3.91 4
 
0.4%
2.68 4
 
0.4%
1.79 4
 
0.4%
4.33 4
 
0.4%
4.95 4
 
0.4%
3.51 4
 
0.4%
8.74 4
 
0.4%
Other values (603) 824
87.7%
ValueCountFrequency (%)
0 78
8.3%
0.01 5
 
0.5%
0.02 1
 
0.1%
0.03 2
 
0.2%
0.04 1
 
0.1%
0.08 1
 
0.1%
0.09 1
 
0.1%
0.1 1
 
0.1%
0.11 1
 
0.1%
0.13 1
 
0.1%
ValueCountFrequency (%)
28.03 1
0.1%
26.72 1
0.1%
25.29 1
0.1%
20.65 1
0.1%
20.4 1
0.1%
19.56 1
0.1%
19.34 1
0.1%
18.98 1
0.1%
18.25 1
0.1%
18.11 1
0.1%

logged_activities_distance
Real number (ℝ)

ZEROS 

Distinct18
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.10812766
Minimum0
Maximum4.94
Zeros908
Zeros (%)96.6%
Negative0
Negative (%)0.0%
Memory size7.5 KiB
2024-01-31T15:14:31.971464image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum4.94
Range4.94
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.61972451
Coefficient of variation (CV)5.7314152
Kurtosis41.315519
Mean0.10812766
Median Absolute Deviation (MAD)0
Skewness6.2989054
Sum101.64
Variance0.38405847
MonotonicityNot monotonic
2024-01-31T15:14:32.241750image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
0 908
96.6%
2.09 9
 
1.0%
2.25 7
 
0.7%
4.91 2
 
0.2%
4.08 1
 
0.1%
2.79 1
 
0.1%
3.17 1
 
0.1%
4.87 1
 
0.1%
4.85 1
 
0.1%
3.29 1
 
0.1%
Other values (8) 8
 
0.9%
ValueCountFrequency (%)
0 908
96.6%
1.96 1
 
0.1%
2.09 9
 
1.0%
2.25 7
 
0.7%
2.79 1
 
0.1%
2.83 1
 
0.1%
3.17 1
 
0.1%
3.29 1
 
0.1%
4.08 1
 
0.1%
4.85 1
 
0.1%
ValueCountFrequency (%)
4.94 1
0.1%
4.93 1
0.1%
4.92 1
0.1%
4.91 2
0.2%
4.89 1
0.1%
4.88 1
0.1%
4.87 1
0.1%
4.86 1
0.1%
4.85 1
0.1%
4.08 1
0.1%

very_active_distance
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct333
Distinct (%)35.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.5026809
Minimum0
Maximum21.92
Zeros413
Zeros (%)43.9%
Negative0
Negative (%)0.0%
Memory size7.5 KiB
2024-01-31T15:14:32.514831image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0.21
Q32.0525
95-th percentile6.403
Maximum21.92
Range21.92
Interquartile range (IQR)2.0525

Descriptive statistics

Standard deviation2.6589412
Coefficient of variation (CV)1.769465
Kurtosis11.910951
Mean1.5026809
Median Absolute Deviation (MAD)0.21
Skewness2.99617
Sum1412.52
Variance7.0699681
MonotonicityNot monotonic
2024-01-31T15:14:32.808419image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 413
43.9%
0.07 9
 
1.0%
0.06 6
 
0.6%
0.14 5
 
0.5%
0.33 5
 
0.5%
0.34 4
 
0.4%
1.06 4
 
0.4%
0.36 4
 
0.4%
1.01 4
 
0.4%
2.79 4
 
0.4%
Other values (323) 482
51.3%
ValueCountFrequency (%)
0 413
43.9%
0.02 2
 
0.2%
0.04 1
 
0.1%
0.05 3
 
0.3%
0.06 6
 
0.6%
0.07 9
 
1.0%
0.08 4
 
0.4%
0.09 1
 
0.1%
0.11 3
 
0.3%
0.12 3
 
0.3%
ValueCountFrequency (%)
21.92 1
0.1%
21.66 1
0.1%
13.4 1
0.1%
13.26 1
0.1%
13.24 1
0.1%
13.22 1
0.1%
13.13 1
0.1%
13.07 1
0.1%
12.79 1
0.1%
12.54 1
0.1%

moderately_active_distance
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct211
Distinct (%)22.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.56754255
Minimum0
Maximum6.48
Zeros386
Zeros (%)41.1%
Negative0
Negative (%)0.0%
Memory size7.5 KiB
2024-01-31T15:14:33.102869image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0.24
Q30.8
95-th percentile2.13
Maximum6.48
Range6.48
Interquartile range (IQR)0.8

Descriptive statistics

Standard deviation0.88358032
Coefficient of variation (CV)1.556853
Kurtosis10.125629
Mean0.56754255
Median Absolute Deviation (MAD)0.24
Skewness2.7711936
Sum533.49
Variance0.78071419
MonotonicityNot monotonic
2024-01-31T15:14:33.388041image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 386
41.1%
0.2 9
 
1.0%
0.28 9
 
1.0%
0.4 9
 
1.0%
0.25 8
 
0.9%
0.31 8
 
0.9%
0.93 8
 
0.9%
0.42 8
 
0.9%
0.27 7
 
0.7%
0.57 7
 
0.7%
Other values (201) 481
51.2%
ValueCountFrequency (%)
0 386
41.1%
0.01 1
 
0.1%
0.02 1
 
0.1%
0.03 3
 
0.3%
0.04 3
 
0.3%
0.05 3
 
0.3%
0.06 3
 
0.3%
0.07 2
 
0.2%
0.08 4
 
0.4%
0.09 2
 
0.2%
ValueCountFrequency (%)
6.48 1
 
0.1%
6.21 1
 
0.1%
5.6 1
 
0.1%
5.4 1
 
0.1%
5.24 1
 
0.1%
5.12 1
 
0.1%
4.58 1
 
0.1%
4.56 1
 
0.1%
4.35 1
 
0.1%
4.22 3
0.3%

light_active_distance
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct491
Distinct (%)52.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.3408191
Minimum0
Maximum10.71
Zeros85
Zeros (%)9.0%
Negative0
Negative (%)0.0%
Memory size7.5 KiB
2024-01-31T15:14:33.828650image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11.945
median3.365
Q34.7825
95-th percentile6.462
Maximum10.71
Range10.71
Interquartile range (IQR)2.8375

Descriptive statistics

Standard deviation2.0406554
Coefficient of variation (CV)0.61082486
Kurtosis-0.18030027
Mean3.3408191
Median Absolute Deviation (MAD)1.42
Skewness0.18224747
Sum3140.37
Variance4.1642744
MonotonicityNot monotonic
2024-01-31T15:14:34.337797image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 85
 
9.0%
4.18 6
 
0.6%
3.17 6
 
0.6%
4.88 6
 
0.6%
3.23 6
 
0.6%
3.94 5
 
0.5%
3.26 5
 
0.5%
0.01 5
 
0.5%
4.46 5
 
0.5%
5.41 5
 
0.5%
Other values (481) 806
85.7%
ValueCountFrequency (%)
0 85
9.0%
0.01 5
 
0.5%
0.02 1
 
0.1%
0.03 3
 
0.3%
0.04 1
 
0.1%
0.06 1
 
0.1%
0.09 1
 
0.1%
0.1 1
 
0.1%
0.11 1
 
0.1%
0.13 2
 
0.2%
ValueCountFrequency (%)
10.71 1
0.1%
10.57 1
0.1%
10.3 1
0.1%
9.48 1
0.1%
9.46 1
0.1%
8.97 1
0.1%
8.79 1
0.1%
8.68 1
0.1%
8.41 1
0.1%
8.27 1
0.1%

sedentary_active_distance
Real number (ℝ)

ZEROS 

Distinct9
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.001606383
Minimum0
Maximum0.11
Zeros858
Zeros (%)91.3%
Negative0
Negative (%)0.0%
Memory size7.5 KiB
2024-01-31T15:14:34.753388image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0.01
Maximum0.11
Range0.11
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.0073461763
Coefficient of variation (CV)4.5731164
Kurtosis99.127444
Mean0.001606383
Median Absolute Deviation (MAD)0
Skewness8.589899
Sum1.51
Variance5.3966306 × 10-5
MonotonicityNot monotonic
2024-01-31T15:14:35.162492image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 858
91.3%
0.01 50
 
5.3%
0.02 21
 
2.2%
0.03 4
 
0.4%
0.05 3
 
0.3%
0.07 1
 
0.1%
0.04 1
 
0.1%
0.11 1
 
0.1%
0.1 1
 
0.1%
ValueCountFrequency (%)
0 858
91.3%
0.01 50
 
5.3%
0.02 21
 
2.2%
0.03 4
 
0.4%
0.04 1
 
0.1%
0.05 3
 
0.3%
0.07 1
 
0.1%
0.1 1
 
0.1%
0.11 1
 
0.1%
ValueCountFrequency (%)
0.11 1
 
0.1%
0.1 1
 
0.1%
0.07 1
 
0.1%
0.05 3
 
0.3%
0.04 1
 
0.1%
0.03 4
 
0.4%
0.02 21
 
2.2%
0.01 50
 
5.3%
0 858
91.3%

very_active_minutes
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct122
Distinct (%)13.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21.164894
Minimum0
Maximum210
Zeros409
Zeros (%)43.5%
Negative0
Negative (%)0.0%
Memory size7.5 KiB
2024-01-31T15:14:35.524183image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4
Q332
95-th percentile93.05
Maximum210
Range210
Interquartile range (IQR)32

Descriptive statistics

Standard deviation32.844803
Coefficient of variation (CV)1.551853
Kurtosis5.7780701
Mean21.164894
Median Absolute Deviation (MAD)4
Skewness2.1761432
Sum19895
Variance1078.7811
MonotonicityNot monotonic
2024-01-31T15:14:35.963200image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 409
43.5%
1 23
 
2.4%
2 18
 
1.9%
3 16
 
1.7%
8 15
 
1.6%
6 14
 
1.5%
11 14
 
1.5%
19 13
 
1.4%
5 13
 
1.4%
14 12
 
1.3%
Other values (112) 393
41.8%
ValueCountFrequency (%)
0 409
43.5%
1 23
 
2.4%
2 18
 
1.9%
3 16
 
1.7%
4 10
 
1.1%
5 13
 
1.4%
6 14
 
1.5%
7 11
 
1.2%
8 15
 
1.6%
9 7
 
0.7%
ValueCountFrequency (%)
210 1
0.1%
207 1
0.1%
200 1
0.1%
194 1
0.1%
186 1
0.1%
184 1
0.1%
137 1
0.1%
132 1
0.1%
129 1
0.1%
125 2
0.2%

fairly_active_minutes
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct81
Distinct (%)8.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.564894
Minimum0
Maximum143
Zeros384
Zeros (%)40.9%
Negative0
Negative (%)0.0%
Memory size7.5 KiB
2024-01-31T15:14:36.402606image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median6
Q319
95-th percentile51
Maximum143
Range143
Interquartile range (IQR)19

Descriptive statistics

Standard deviation19.987404
Coefficient of variation (CV)1.4734656
Kurtosis7.9957314
Mean13.564894
Median Absolute Deviation (MAD)6
Skewness2.479492
Sum12751
Variance399.49632
MonotonicityNot monotonic
2024-01-31T15:14:36.751519image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 384
40.9%
8 36
 
3.8%
6 23
 
2.4%
5 23
 
2.4%
16 22
 
2.3%
7 20
 
2.1%
10 19
 
2.0%
9 19
 
2.0%
13 18
 
1.9%
11 18
 
1.9%
Other values (71) 358
38.1%
ValueCountFrequency (%)
0 384
40.9%
1 10
 
1.1%
2 8
 
0.9%
3 9
 
1.0%
4 14
 
1.5%
5 23
 
2.4%
6 23
 
2.4%
7 20
 
2.1%
8 36
 
3.8%
9 19
 
2.0%
ValueCountFrequency (%)
143 1
 
0.1%
125 1
 
0.1%
122 1
 
0.1%
116 1
 
0.1%
115 1
 
0.1%
113 1
 
0.1%
98 1
 
0.1%
96 1
 
0.1%
95 5
0.5%
94 1
 
0.1%

lightly_active_minutes
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct335
Distinct (%)35.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean192.81277
Minimum0
Maximum518
Zeros84
Zeros (%)8.9%
Negative0
Negative (%)0.0%
Memory size7.5 KiB
2024-01-31T15:14:37.070840image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1127
median199
Q3264
95-th percentile369.05
Maximum518
Range518
Interquartile range (IQR)137

Descriptive statistics

Standard deviation109.1747
Coefficient of variation (CV)0.56622132
Kurtosis-0.36011793
Mean192.81277
Median Absolute Deviation (MAD)69
Skewness-0.037929343
Sum181244
Variance11919.115
MonotonicityNot monotonic
2024-01-31T15:14:37.388529image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 84
 
8.9%
206 12
 
1.3%
258 10
 
1.1%
195 9
 
1.0%
214 8
 
0.9%
139 7
 
0.7%
238 7
 
0.7%
141 7
 
0.7%
199 7
 
0.7%
227 7
 
0.7%
Other values (325) 782
83.2%
ValueCountFrequency (%)
0 84
8.9%
1 3
 
0.3%
2 4
 
0.4%
3 3
 
0.3%
4 1
 
0.1%
9 3
 
0.3%
10 2
 
0.2%
11 1
 
0.1%
12 2
 
0.2%
15 1
 
0.1%
ValueCountFrequency (%)
518 1
0.1%
513 1
0.1%
512 1
0.1%
487 1
0.1%
480 1
0.1%
475 1
0.1%
461 1
0.1%
458 1
0.1%
448 1
0.1%
439 1
0.1%

sedentary_minutes
Real number (ℝ)

HIGH CORRELATION 

Distinct549
Distinct (%)58.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean991.21064
Minimum0
Maximum1440
Zeros1
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size7.5 KiB
2024-01-31T15:14:37.679034image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile536.7
Q1729.75
median1057.5
Q31229.5
95-th percentile1440
Maximum1440
Range1440
Interquartile range (IQR)499.75

Descriptive statistics

Standard deviation301.26744
Coefficient of variation (CV)0.30393887
Kurtosis-0.66595003
Mean991.21064
Median Absolute Deviation (MAD)261
Skewness-0.29449809
Sum931738
Variance90762.068
MonotonicityNot monotonic
2024-01-31T15:14:37.980859image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1440 79
 
8.4%
1182 7
 
0.7%
692 6
 
0.6%
1112 5
 
0.5%
1131 5
 
0.5%
1122 5
 
0.5%
1105 5
 
0.5%
709 5
 
0.5%
1119 5
 
0.5%
728 5
 
0.5%
Other values (539) 813
86.5%
ValueCountFrequency (%)
0 1
0.1%
2 1
0.1%
13 1
0.1%
48 1
0.1%
111 1
0.1%
125 1
0.1%
127 1
0.1%
218 1
0.1%
222 1
0.1%
241 1
0.1%
ValueCountFrequency (%)
1440 79
8.4%
1439 3
 
0.3%
1438 3
 
0.3%
1437 2
 
0.2%
1431 1
 
0.1%
1430 2
 
0.2%
1428 1
 
0.1%
1423 1
 
0.1%
1420 1
 
0.1%
1413 1
 
0.1%

calories
Real number (ℝ)

HIGH CORRELATION 

Distinct734
Distinct (%)78.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2303.6096
Minimum0
Maximum4900
Zeros4
Zeros (%)0.4%
Negative0
Negative (%)0.0%
Memory size7.5 KiB
2024-01-31T15:14:38.303955image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1372.85
Q11828.5
median2134
Q32793.25
95-th percentile3654.25
Maximum4900
Range4900
Interquartile range (IQR)964.75

Descriptive statistics

Standard deviation718.16686
Coefficient of variation (CV)0.3117572
Kurtosis0.62502694
Mean2303.6096
Median Absolute Deviation (MAD)467
Skewness0.42245048
Sum2165393
Variance515763.64
MonotonicityNot monotonic
2024-01-31T15:14:38.595200image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1980 13
 
1.4%
2063 11
 
1.2%
1841 9
 
1.0%
1688 9
 
1.0%
1347 8
 
0.9%
2225 4
 
0.4%
1819 4
 
0.4%
2044 4
 
0.4%
1922 4
 
0.4%
0 4
 
0.4%
Other values (724) 870
92.6%
ValueCountFrequency (%)
0 4
0.4%
52 1
 
0.1%
57 1
 
0.1%
120 1
 
0.1%
257 1
 
0.1%
403 1
 
0.1%
665 1
 
0.1%
741 1
 
0.1%
928 1
 
0.1%
1002 1
 
0.1%
ValueCountFrequency (%)
4900 1
0.1%
4552 1
0.1%
4547 1
0.1%
4546 1
0.1%
4501 1
0.1%
4398 1
0.1%
4392 1
0.1%
4274 1
0.1%
4236 1
0.1%
4163 1
0.1%

total_minutes_asleep
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct256
Distinct (%)62.4%
Missing530
Missing (%)56.4%
Infinite0
Infinite (%)0.0%
Mean419.17317
Minimum58
Maximum796
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.5 KiB
2024-01-31T15:14:38.893334image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum58
5-th percentile168.25
Q1361
median432.5
Q3490
95-th percentile590.55
Maximum796
Range738
Interquartile range (IQR)129

Descriptive statistics

Standard deviation118.63592
Coefficient of variation (CV)0.28302364
Kurtosis1.5975686
Mean419.17317
Median Absolute Deviation (MAD)64.5
Skewness-0.60913426
Sum171861
Variance14074.481
MonotonicityNot monotonic
2024-01-31T15:14:39.201825image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
442 7
 
0.7%
441 5
 
0.5%
412 5
 
0.5%
357 4
 
0.4%
531 4
 
0.4%
523 4
 
0.4%
354 4
 
0.4%
322 4
 
0.4%
508 4
 
0.4%
421 4
 
0.4%
Other values (246) 365
38.8%
(Missing) 530
56.4%
ValueCountFrequency (%)
58 1
0.1%
59 1
0.1%
61 1
0.1%
62 1
0.1%
74 2
0.2%
77 1
0.1%
79 1
0.1%
82 1
0.1%
98 1
0.1%
99 1
0.1%
ValueCountFrequency (%)
796 1
0.1%
775 1
0.1%
750 1
0.1%
722 1
0.1%
700 1
0.1%
692 1
0.1%
681 1
0.1%
658 2
0.2%
651 1
0.1%
644 1
0.1%

total_sleep_records
Categorical

IMBALANCE  MISSING 

Distinct3
Distinct (%)0.7%
Missing530
Missing (%)56.4%
Memory size7.5 KiB
1.0
364 
2.0
43 
3.0
 
3

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters1230
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1.0
2nd row2.0
3rd row1.0
4th row2.0
5th row1.0

Common Values

ValueCountFrequency (%)
1.0 364
38.7%
2.0 43
 
4.6%
3.0 3
 
0.3%
(Missing) 530
56.4%

Length

2024-01-31T15:14:39.482802image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-31T15:14:39.735206image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
1.0 364
88.8%
2.0 43
 
10.5%
3.0 3
 
0.7%

Most occurring characters

ValueCountFrequency (%)
. 410
33.3%
0 410
33.3%
1 364
29.6%
2 43
 
3.5%
3 3
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 820
66.7%
Other Punctuation 410
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 410
50.0%
1 364
44.4%
2 43
 
5.2%
3 3
 
0.4%
Other Punctuation
ValueCountFrequency (%)
. 410
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1230
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 410
33.3%
0 410
33.3%
1 364
29.6%
2 43
 
3.5%
3 3
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1230
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 410
33.3%
0 410
33.3%
1 364
29.6%
2 43
 
3.5%
3 3
 
0.2%

total_time_in_bed
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct242
Distinct (%)59.0%
Missing530
Missing (%)56.4%
Infinite0
Infinite (%)0.0%
Mean458.48293
Minimum61
Maximum961
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.5 KiB
2024-01-31T15:14:39.994256image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum61
5-th percentile210.05
Q1403.75
median463
Q3526
95-th percentile630.4
Maximum961
Range900
Interquartile range (IQR)122.25

Descriptive statistics

Standard deviation127.45514
Coefficient of variation (CV)0.27799321
Kurtosis3.4727052
Mean458.48293
Median Absolute Deviation (MAD)61
Skewness-0.2152768
Sum187978
Variance16244.813
MonotonicityNot monotonic
2024-01-31T15:14:40.295972image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
546 6
 
0.6%
402 5
 
0.5%
458 5
 
0.5%
510 5
 
0.5%
545 4
 
0.4%
961 4
 
0.4%
501 4
 
0.4%
522 4
 
0.4%
461 4
 
0.4%
457 4
 
0.4%
Other values (232) 365
38.8%
(Missing) 530
56.4%
ValueCountFrequency (%)
61 1
0.1%
65 2
0.2%
69 1
0.1%
75 1
0.1%
77 1
0.1%
78 1
0.1%
82 1
0.1%
85 1
0.1%
104 1
0.1%
107 1
0.1%
ValueCountFrequency (%)
961 4
0.4%
843 1
 
0.1%
775 1
 
0.1%
725 1
 
0.1%
722 1
 
0.1%
712 1
 
0.1%
704 1
 
0.1%
698 1
 
0.1%
689 1
 
0.1%
686 2
0.2%

bmi
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct36
Distinct (%)53.7%
Missing873
Missing (%)92.9%
Infinite0
Infinite (%)0.0%
Mean25.185224
Minimum21.45
Maximum47.54
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.5 KiB
2024-01-31T15:14:40.549936image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum21.45
5-th percentile23.001
Q123.96
median24.39
Q325.56
95-th percentile27.429
Maximum47.54
Range26.09
Interquartile range (IQR)1.6

Descriptive statistics

Standard deviation3.0669624
Coefficient of variation (CV)0.12177626
Kurtosis43.824925
Mean25.185224
Median Absolute Deviation (MAD)0.92
Skewness6.0002424
Sum1687.41
Variance9.4062587
MonotonicityNot monotonic
2024-01-31T15:14:41.216710image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
24 5
 
0.5%
23.89 5
 
0.5%
23.96 5
 
0.5%
25.59 4
 
0.4%
25.41 4
 
0.4%
25.56 4
 
0.4%
24.1 4
 
0.4%
24.24 2
 
0.2%
24.17 2
 
0.2%
25.68 2
 
0.2%
Other values (26) 30
 
3.2%
(Missing) 873
92.9%
ValueCountFrequency (%)
21.45 1
 
0.1%
21.69 1
 
0.1%
22.65 2
 
0.2%
23.82 2
 
0.2%
23.85 1
 
0.1%
23.89 5
0.5%
23.93 1
 
0.1%
23.96 5
0.5%
24 5
0.5%
24.1 4
0.4%
ValueCountFrequency (%)
47.54 1
0.1%
28 1
0.1%
27.46 1
0.1%
27.45 1
0.1%
27.38 1
0.1%
27.32 1
0.1%
27.25 1
0.1%
27.04 1
0.1%
27 1
0.1%
25.68 2
0.2%

weight_kg
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct34
Distinct (%)50.7%
Missing873
Missing (%)92.9%
Infinite0
Infinite (%)0.0%
Mean72.035821
Minimum52.6
Maximum133.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.5 KiB
2024-01-31T15:14:41.475776image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum52.6
5-th percentile58.41
Q161.4
median62.5
Q385.05
95-th percentile85.71
Maximum133.5
Range80.9
Interquartile range (IQR)23.65

Descriptive statistics

Standard deviation13.923206
Coefficient of variation (CV)0.1932817
Kurtosis3.8619516
Mean72.035821
Median Absolute Deviation (MAD)6.7
Skewness1.3696693
Sum4826.4
Variance193.85567
MonotonicityNot monotonic
2024-01-31T15:14:41.798005image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
61.2 5
 
0.5%
61.4 5
 
0.5%
61.5 5
 
0.5%
85.5 5
 
0.5%
85.4 4
 
0.4%
61.7 4
 
0.4%
84.9 4
 
0.4%
61.9 2
 
0.2%
52.6 2
 
0.2%
62.1 2
 
0.2%
Other values (24) 29
 
3.1%
(Missing) 873
92.9%
ValueCountFrequency (%)
52.6 2
 
0.2%
56.7 1
 
0.1%
57.3 1
 
0.1%
61 2
 
0.2%
61.1 1
 
0.1%
61.2 5
0.5%
61.3 1
 
0.1%
61.4 5
0.5%
61.5 5
0.5%
61.7 4
0.4%
ValueCountFrequency (%)
133.5 1
 
0.1%
90.7 1
 
0.1%
85.8 2
 
0.2%
85.5 5
0.5%
85.4 4
0.4%
85.3 2
 
0.2%
85.1 2
 
0.2%
85 1
 
0.1%
84.9 4
0.4%
84.5 2
 
0.2%

weight_pounds
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct34
Distinct (%)50.7%
Missing873
Missing (%)92.9%
Infinite0
Infinite (%)0.0%
Mean158.81075
Minimum115.96
Maximum294.32
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.5 KiB
2024-01-31T15:14:42.351570image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum115.96
5-th percentile128.768
Q1135.36
median137.79
Q3187.5
95-th percentile188.962
Maximum294.32
Range178.36
Interquartile range (IQR)52.14

Descriptive statistics

Standard deviation30.695989
Coefficient of variation (CV)0.1932866
Kurtosis3.8622282
Mean158.81075
Median Absolute Deviation (MAD)14.77
Skewness1.369708
Sum10640.32
Variance942.24375
MonotonicityNot monotonic
2024-01-31T15:14:42.607375image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
134.92 5
 
0.5%
135.36 5
 
0.5%
135.58 5
 
0.5%
188.5 5
 
0.5%
188.27 4
 
0.4%
136.03 4
 
0.4%
187.17 4
 
0.4%
136.47 2
 
0.2%
115.96 2
 
0.2%
136.91 2
 
0.2%
Other values (24) 29
 
3.1%
(Missing) 873
92.9%
ValueCountFrequency (%)
115.96 2
 
0.2%
125 1
 
0.1%
126.32 1
 
0.1%
134.48 2
 
0.2%
134.7 1
 
0.1%
134.92 5
0.5%
135.14 1
 
0.1%
135.36 5
0.5%
135.58 5
0.5%
136.03 4
0.4%
ValueCountFrequency (%)
294.32 1
 
0.1%
199.96 1
 
0.1%
189.16 2
 
0.2%
188.5 5
0.5%
188.27 4
0.4%
188.05 2
 
0.2%
187.61 2
 
0.2%
187.39 1
 
0.1%
187.17 4
0.4%
186.29 2
 
0.2%

activity_level
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size7.5 KiB
Very Active
531 
Lightly Active
295 
Sedentary Active
84 
Moderately Active
 
30

Length

Max length17
Median length11
Mean length12.579787
Min length11

Characters and Unicode

Total characters11825
Distinct characters20
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowVery Active
2nd rowVery Active
3rd rowVery Active
4th rowVery Active
5th rowVery Active

Common Values

ValueCountFrequency (%)
Very Active 531
56.5%
Lightly Active 295
31.4%
Sedentary Active 84
 
8.9%
Moderately Active 30
 
3.2%

Length

2024-01-31T15:14:42.901876image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-31T15:14:43.160182image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
active 940
50.0%
very 531
28.2%
lightly 295
 
15.7%
sedentary 84
 
4.5%
moderately 30
 
1.6%

Most occurring characters

ValueCountFrequency (%)
e 1699
14.4%
t 1349
11.4%
i 1235
10.4%
y 940
7.9%
940
7.9%
A 940
7.9%
c 940
7.9%
v 940
7.9%
r 645
 
5.5%
V 531
 
4.5%
Other values (10) 1666
14.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 9005
76.2%
Uppercase Letter 1880
 
15.9%
Space Separator 940
 
7.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 1699
18.9%
t 1349
15.0%
i 1235
13.7%
y 940
10.4%
c 940
10.4%
v 940
10.4%
r 645
 
7.2%
l 325
 
3.6%
h 295
 
3.3%
g 295
 
3.3%
Other values (4) 342
 
3.8%
Uppercase Letter
ValueCountFrequency (%)
A 940
50.0%
V 531
28.2%
L 295
 
15.7%
S 84
 
4.5%
M 30
 
1.6%
Space Separator
ValueCountFrequency (%)
940
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 10885
92.1%
Common 940
 
7.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 1699
15.6%
t 1349
12.4%
i 1235
11.3%
y 940
8.6%
A 940
8.6%
c 940
8.6%
v 940
8.6%
r 645
 
5.9%
V 531
 
4.9%
l 325
 
3.0%
Other values (9) 1341
12.3%
Common
ValueCountFrequency (%)
940
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11825
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 1699
14.4%
t 1349
11.4%
i 1235
10.4%
y 940
7.9%
940
7.9%
A 940
7.9%
c 940
7.9%
v 940
7.9%
r 645
 
5.5%
V 531
 
4.5%
Other values (10) 1666
14.1%

Interactions

2024-01-31T15:14:20.337895image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:12:27.220654image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:12:32.580169image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:12:41.134884image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:12:50.659913image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:12:57.936027image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:13:05.794196image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:13:10.990835image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:13:16.384675image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:13:22.275252image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:13:27.103251image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:13:32.961979image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:13:38.475223image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:13:44.186812image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:13:49.440080image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:13:54.486018image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:14:00.891496image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:14:05.668219image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:14:11.269548image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:14:15.614661image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:14:20.582071image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:12:27.488573image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:12:32.836537image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:12:41.615381image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:12:51.409869image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:12:58.204077image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:13:06.177912image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:13:11.244899image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:13:16.735104image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:13:22.530324image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:13:27.353774image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:13:33.223236image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:13:38.746478image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:13:44.588781image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:13:49.702378image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:13:54.742324image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:14:01.143934image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:14:05.924135image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:14:11.492504image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:14:15.860048image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:14:21.803292image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:12:27.782130image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:12:33.062943image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:12:42.027979image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:12:52.250752image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:12:58.432705image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:13:06.460602image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:13:11.470960image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:13:16.982893image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:13:22.769025image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:13:27.586594image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:13:33.994020image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:13:39.002858image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:13:44.958061image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:13:49.950078image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:13:54.966159image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:14:01.368321image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:14:06.137459image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:14:11.694682image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:14:16.071207image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:14:22.178047image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:12:28.162441image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:12:33.288213image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:12:42.489302image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:12:53.181907image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:12:58.690153image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:13:06.730068image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:13:11.726759image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:13:17.318871image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:13:23.031854image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:13:27.857370image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:13:34.256487image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:13:39.269707image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:13:45.292888image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:13:50.223318image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:13:56.045865image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:14:01.590168image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:14:06.347856image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:14:11.915112image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:14:16.315604image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:14:22.538165image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:12:28.423510image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:12:33.540099image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:12:42.943612image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:12:53.720183image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:13:01.057361image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:13:06.966683image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:13:11.983235image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:13:17.687018image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:13:23.289975image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:13:28.103877image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:13:34.495198image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:13:39.514616image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:13:45.538982image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:13:50.481087image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:13:56.380342image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:14:01.862403image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:14:06.589263image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:14:12.134753image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:14:16.543997image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:14:22.834681image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:12:28.669000image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:12:33.765573image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:12:43.455050image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:12:54.175993image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:13:01.304934image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:13:07.233985image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:13:12.227929image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:13:18.096163image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:13:23.537076image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:13:28.344504image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:13:34.757746image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:13:39.758182image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:13:45.793741image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:13:50.742549image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:13:56.774302image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:14:02.118494image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:14:06.827502image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:14:12.341487image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:14:16.759074image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:14:23.195588image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:12:28.917529image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:12:33.993452image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:12:43.998383image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:12:54.437056image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:13:01.568766image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:13:07.484801image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:13:12.469038image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:13:18.494127image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:13:23.789140image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:13:28.595320image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:13:35.006971image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:13:40.035177image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:13:46.049481image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:13:50.995908image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:13:57.138471image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:14:02.381182image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:14:07.086573image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:14:12.590074image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:14:17.010004image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:14:23.530818image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:12:29.184496image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:12:34.206369image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:12:44.568186image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:12:54.685072image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:13:01.812017image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:13:07.748523image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:13:12.716636image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:13:18.840817image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:13:24.029092image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
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2024-01-31T15:13:37.745661image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:13:43.159954image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:13:48.780916image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:13:53.785479image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:14:00.164115image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:14:05.026406image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:14:10.405232image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:14:14.952860image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:14:19.609685image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:14:26.061971image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:12:32.086679image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:12:40.337001image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:12:49.688026image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:12:57.452192image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:13:05.116203image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:13:10.475441image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:13:15.900464image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:13:21.796737image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:13:26.639602image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:13:32.470911image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:13:37.983200image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:13:43.491475image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:13:48.981318image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:13:54.004086image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:14:00.385889image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:14:05.221713image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:14:10.781471image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:14:15.145862image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:14:19.829154image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:14:26.307790image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:12:32.344410image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:12:40.751569image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:12:50.099410image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:12:57.701097image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:13:05.453413image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:13:10.735678image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:13:16.144208image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:13:22.036602image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:13:26.871724image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:13:32.730400image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:13:38.238215image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:13:43.834642image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:13:49.204869image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:13:54.240304image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:14:00.647788image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:14:05.452450image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:14:11.038541image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:14:15.392058image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-01-31T15:14:20.080370image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Correlations

2024-01-31T15:14:43.409866image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
activity_levelbmicaloriesdaily_average_heartratefairly_active_minutesidlight_active_distancelightly_active_minuteslogged_activities_distancemoderately_active_distancesedentary_active_distancesedentary_minutestotal_distancetotal_minutes_asleeptotal_sleep_recordstotal_stepstotal_time_in_bedtracker_distancevery_active_distancevery_active_minutesweight_kgweight_pounds
activity_level1.0000.0380.439-0.0220.8270.1870.2440.1160.1590.828-0.085-0.1620.620-0.2110.1130.616-0.1950.6200.8620.8670.1760.176
bmi0.0381.0000.5370.261-0.2660.2640.206-0.163-0.104-0.2910.0140.5980.2000.1930.0000.1670.1920.2130.2120.2770.8950.895
calories0.4390.5371.0000.0290.4350.4290.4650.2860.2260.4030.010-0.1520.617-0.0390.0000.559-0.1790.6170.4970.5400.7180.718
daily_average_heartrate-0.0220.2610.0291.000-0.0060.0810.0780.2650.259-0.0190.0410.4020.023-0.0660.0500.055-0.0980.013-0.020-0.0290.1840.184
fairly_active_minutes0.827-0.2660.435-0.0061.0000.1250.3450.2320.1330.980-0.103-0.3140.685-0.2510.0460.689-0.1830.6860.7430.746-0.253-0.253
id0.1870.2640.4290.0810.1251.0000.030-0.0840.2100.111-0.114-0.0640.1990.1140.1000.158-0.0030.1970.2230.2510.6000.600
light_active_distance0.2440.2060.4650.0780.3450.0301.0000.8780.1390.3610.142-0.4660.715-0.0740.0000.715-0.1200.7140.2850.2850.3640.364
lightly_active_minutes0.116-0.1630.2860.2650.232-0.0840.8781.0000.0570.2440.194-0.4800.5590.0140.0000.581-0.0420.5580.1580.152-0.269-0.269
logged_activities_distance0.159-0.1040.2260.2590.1330.2100.1390.0571.0000.1570.010-0.0870.203-0.1030.0000.180-0.1300.1930.2260.265-0.104-0.104
moderately_active_distance0.828-0.2910.403-0.0190.9800.1110.3610.2440.1571.000-0.096-0.3080.701-0.2570.0000.704-0.1810.7010.7490.734-0.293-0.293
sedentary_active_distance-0.0850.0140.0100.041-0.103-0.1140.1420.1940.010-0.0961.0000.0960.013-0.0670.0000.015-0.0860.011-0.064-0.0570.0950.095
sedentary_minutes-0.1620.598-0.1520.402-0.314-0.064-0.466-0.480-0.087-0.3080.0961.000-0.414-0.5680.000-0.428-0.602-0.415-0.235-0.2410.6260.626
total_distance0.6200.2000.6170.0230.6850.1990.7150.5590.2030.7010.013-0.4141.000-0.2210.0880.992-0.1991.0000.7760.7520.4230.423
total_minutes_asleep-0.2110.193-0.039-0.066-0.2510.114-0.0740.014-0.103-0.257-0.067-0.568-0.2211.0000.259-0.2250.917-0.222-0.215-0.2300.1930.193
total_sleep_records0.1130.0000.0000.0500.0460.1000.0000.0000.0000.0000.0000.0000.0880.2591.000-0.1580.109-0.146-0.145-0.1580.2100.210
total_steps0.6160.1670.5590.0550.6890.1580.7150.5810.1800.7040.015-0.4280.992-0.225-0.1581.000-0.1960.9920.7700.7490.3730.373
total_time_in_bed-0.1950.192-0.179-0.098-0.183-0.003-0.120-0.042-0.130-0.181-0.086-0.602-0.1990.9170.109-0.1961.000-0.199-0.207-0.2350.1920.192
tracker_distance0.6200.2130.6170.0130.6860.1970.7140.5580.1930.7010.011-0.4151.000-0.222-0.1460.992-0.1991.0000.7750.7510.4380.438
very_active_distance0.8620.2120.497-0.0200.7430.2230.2850.1580.2260.749-0.064-0.2350.776-0.215-0.1450.770-0.2070.7751.0000.9700.4310.431
very_active_minutes0.8670.2770.540-0.0290.7460.2510.2850.1520.2650.734-0.057-0.2410.752-0.230-0.1580.749-0.2350.7510.9701.0000.5080.508
weight_kg0.1760.8950.7180.184-0.2530.6000.364-0.269-0.104-0.2930.0950.6260.4230.1930.2100.3730.1920.4380.4310.5081.0001.000
weight_pounds0.1760.8950.7180.184-0.2530.6000.364-0.269-0.104-0.2930.0950.6260.4230.1930.2100.3730.1920.4380.4310.5081.0001.000

Missing values

2024-01-31T15:14:26.694246image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-31T15:14:27.389850image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2024-01-31T15:14:27.844629image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

idactivity_datedaily_average_heartratetotal_stepstotal_distancetracker_distancelogged_activities_distancevery_active_distancemoderately_active_distancelight_active_distancesedentary_active_distancevery_active_minutesfairly_active_minuteslightly_active_minutessedentary_minutescaloriestotal_minutes_asleeptotal_sleep_recordstotal_time_in_bedbmiweight_kgweight_poundsactivity_level
015039603662016-04-12NaN131628.508.500.001.880.556.060.0025133287281985327.001.00346.00NaNNaNNaNVery Active
115039603662016-04-13NaN107356.976.970.001.570.694.710.0021192177761797384.002.00407.00NaNNaNNaNVery Active
215039603662016-04-14NaN104606.746.740.002.440.403.910.00301118112181776NaNNaNNaNNaNNaNNaNVery Active
315039603662016-04-15NaN97626.286.280.002.141.262.830.0029342097261745412.001.00442.00NaNNaNNaNVery Active
415039603662016-04-16NaN126698.168.160.002.710.415.040.0036102217731863340.002.00367.00NaNNaNNaNVery Active
515039603662016-04-17NaN97056.486.480.003.190.782.510.0038201645391728700.001.00712.00NaNNaNNaNVery Active
615039603662016-04-18NaN130198.598.590.003.250.644.710.00421623311491921NaNNaNNaNNaNNaNNaNVery Active
715039603662016-04-19NaN155069.889.880.003.531.325.030.0050312647752035304.001.00320.00NaNNaNNaNVery Active
815039603662016-04-20NaN105446.686.680.001.960.484.240.0028122058181786360.001.00377.00NaNNaNNaNVery Active
915039603662016-04-21NaN98196.346.340.001.340.354.650.001982118381775325.001.00364.00NaNNaNNaNVery Active
idactivity_datedaily_average_heartratetotal_stepstotal_distancetracker_distancelogged_activities_distancevery_active_distancemoderately_active_distancelight_active_distancesedentary_active_distancevery_active_minutesfairly_active_minuteslightly_active_minutessedentary_minutescaloriestotal_minutes_asleeptotal_sleep_recordstotal_time_in_bedbmiweight_kgweight_poundsactivity_level
93088776893912016-05-0366.39108188.218.210.001.390.106.670.0119322911892817NaNNaNNaN25.4184.90187.17Very Active
93188776893912016-05-0476.771819316.3016.300.0010.420.315.530.0066821211543477NaNNaNNaN25.2684.40186.07Very Active
93288776893912016-05-0571.331405510.6710.670.005.460.824.370.00671518811703052NaNNaNNaNNaNNaNNaNVery Active
93388776893912016-05-0682.982172719.3419.340.0012.790.296.160.00961723210954015NaNNaNNaN25.4485.00187.39Very Active
93488776893912016-05-0786.44123328.138.130.000.080.966.990.001052827110364142NaNNaNNaNNaNNaNNaNVery Active
93588776893912016-05-0871.59106868.118.110.001.080.206.800.0017424511742847NaNNaNNaN25.5685.40188.27Very Active
93688776893912016-05-0979.572022618.2518.250.0011.100.806.240.05731921711313710NaNNaNNaN25.6185.50188.50Very Active
93788776893912016-05-1070.73107338.158.150.001.350.466.280.00181122411872832NaNNaNNaNNaNNaNNaNVery Active
93888776893912016-05-1178.402142019.5619.560.0013.220.415.890.00881221311273832NaNNaNNaN25.5685.40188.27Very Active
93988776893912016-05-1269.9280646.126.120.001.820.044.250.002311377701849NaNNaNNaN25.1484.00185.19Very Active